1. Field of the Invention
The present invention relates to a device for determining the distance between vehicles, using light sensors with light sensor arrays.
2. Description of the Related Art
As an example of a device for determining the distance between vehicles, there is known a device which electrically compares images formed by two right and left optical systems and then determines the distance between moving vehicles using the principle of triangulation. FIG. 12 shows an arrangement of a conventional device for measuring the distance between moving vehicles. In this device, imaging lenses 1 and 2 are disposed with their optical axes separated a distance B, and light sensor arrays 3A and 4A, each of which is a CCD linear array sensor, are spaced from the respective imaging lenses 1 and 2 by their focal length f. The light sensor arrays 3A and 4A output image signals 30A and 40A that represent images formed on the respective sensor arrays to a signal processor 5, which comprises amplifiers 51 and 52, analog-to-digital (A/D) converters 53 and 54, and a storage device 55. The image signals 30A and 40A are amplified by the amplifiers 51 and 52, converted into digital data by the A/D converters 53 and 54, and then stored in the storage device 55 as image data 31A and 41A. A distance detector 7, which is a microprocessor-based circuit, compares the right and left image data 31A and 41A stored in the storage device 55 to calculate the distance to the object and then outputs a distance signal 10 to the outside.
The principle of distance calculation will be described next with reference to FIG. 13. Take X-axis and the Y-axis, respectively as the axis of abscissa and the axis of ordinate, with the origin O at the middle point between the imaging lenses 1 and 2. Next, let the coordinates of position L1 where the image of object 11A is formed on the light sensor array 3A be (-a.sub.L1 -B/2, -f) and let the coordinates of position R.sub.1 where the object image is formed on the right light sensor array 4A be (a.sub.R1 +B/2, -f). The coordinates of the center O.sub.L of the lens 1 are (-B/2, 0) and the coordinates of the center O.sub.R of the lens 2 is (B/2, 0). Assume the coordinates of a point M on the object 11A are (x, y). Then, the coordinates of the point N at which the perpendicular dropped from the point M onto the X-axis and the X-axis intersect will be (x, 0). The coordinates of the foot L.sub.0 of the perpendicular dropped from the point O.sub.L onto the sensor array 3A are (-B/2, -f), and the coordinates of the foot R.sub.0 of the perpendicular dropped from the point O.sub.R onto the sensor array 4A are (B/2, -f). Note here that, in the figure, a.sub.L1 represents the distance between points L.sub.0 and L.sub.1, and a.sub.R1 represents the distance between points R.sub.0 and R.sub.1. Since triangles MO.sub.L N and O.sub.L L.sub.1 L.sub.0 are similar and triangles MO.sub.R N and O.sub.R R.sub.1 R.sub.0 are similar, the following equations will hold: EQU (x+B/2).multidot.f=a.sub.L1 .multidot.y (1) EQU (x-B/2).multidot.f=a.sub.R1 .multidot.y (2)
From equations (1) and (2) the following equation is obtained: EQU y=B.multidot.f/(a.sub.L1 +a.sub.R1) (3)
If, therefore, the values of a.sub.L1 (the distance between left image location L.sub.1 and point L.sub.0) and a.sub.R1 (the distance between right image location R.sub.1 and point R.sub.0) are known, then the distance y to the object 11A can be determined.
Next, the operation of the distance detector 7 will be described with reference to FIGS. 14 and 15. FIG. 14 illustrates the left image data 31A output from the A/D converter 53 and the right image data 41A output from the A/D converter 54. FIG. 15 is a schematic representation of a normal image at the time of detection of the distance to a vehicle 11 ahead. The distance detector 7 sets a measuring range 9 within the field of view as shown in FIG. 15 and compares the left and right image data 31A and 41A within this measuring range. When the comparison shows no match between the right and left images, the left image data 31A is shifted to the right and the right image data 41A is shifted to the left, as shown by broken lines in FIG. 14, to obtain the amounts of shift when the image match occurs. The distance a.sub.L1 between the left image location L.sub.1 and the point L.sub.0 corresponds to the amount of shift of the left image and the distance a.sub.R1 between the right image location R.sub.1 and the point R.sub.0 corresponds to the amount of shift of the right image. The distance detector 7 is thus allowed to calculate the distance to the object 11A (a vehicle 11 ahead) from equation (3) using the shift amounts a.sub.L1 and a.sub.R1.
In the prior art, however, problems arise in the following cases. FIG. 16 illustrates an abnormal image at the time of detection of the distance to the vehicle 11 ahead. At the vehicle interval detection time, as shown in FIG. 16, a part of the vehicle 11 ahead may go out of the measuring range 9 when the leading vehicle 11 or the trailing vehicle (distance measuring vehicle) strays from the center or when they are moving on a curved path. Alternatively, a part of the leading vehicle 11 and a part of a vehicle 13 moving on another traffic lane may appear simultaneously within the same measuring range 9. In either case, not only will unstable and inaccurate measurement be made, but the measurement itself will become meaningless.
To solve this problem, an automatic tracking system may be used which holds the measuring range locked on the vehicle ahead all the time. However, this automatic tracking system requires a long time for image processing for tracking. For this reason, except when the leading vehicle is moving at a constant speed, the system cannot generally measure the distance to the vehicle ahead, which varies according to its speed. This problem could be solved technically by using a high-speed image processing technique. However, this would inevitably increase the size and cost of the device. It is thus almost impossible to implement the automatic tracking system.